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Activity Number: 413 - Consulting, Collaboration, Communication, and Impact
Type: Contributed
Date/Time: Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Consulting
Abstract #322613 View Presentation
Title: Ensuring Reproducibility of Collaborative Projects: Statisticians Taking the Lead
Author(s): Rachel Jia* and Madhu Mazumdar and John Mandeli and Meng Ru
Companies: Icahn School of Medicine at Mount Sinai and Icahn School of Medicine at Mount Sinai and Icahn School of Medicine at Mount Sinai and Icahn School of Medicine at Mount Sinai
Keywords: Reproducibility ; cancer biology ; Biostatistics shared resource facility ; cancer center ; open science
Abstract:

'Statistical Challenges in Assessing and Fostering the Reproducibility of Scientific Results'(NAM press, 2016) stresses that sharing of i) data, ii) statistical code, and iii) dynamic reporting (DR) are essential for ensuring reproducibility of research (RR). In the field of oncology, RR defined as the ability of others to reproduce the published findings, given the original data, has been problematic. We hypothesize that readiness of statisticians with 1) knowledge of tools for making a collaborative project easy to share and 2) leadership skills for engaging collaborators with discussion about the issue of non-RR are essential for improvement. We took 3 steps at a cancer center biostatistics core: 1) trained statisticians on data archiving and dynamic report generation (R, R Markdown, Knitr); 2) developed illustrative examples of studies with longitudinally collected quality of life endpoints and with assessment of prognostic value of gene signature; both needed repeated data updates and benefitted from DR; 3) organized a 'Rigor and Reproducibility Journal Club" for discussion, collaboration, and training. We will discuss emerging successes and barriers.


Authors who are presenting talks have a * after their name.

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